电力系统自动化2026，Vol.50Issue(8)：106-115,10.DOI:10.7500/AEPS20250617005
自主调峰下风火荷储容量优化配置方法
Optimal Capacity Allocation Method for Wind-Thermal-Load-Storage Under Autonomous Peak-shaving
摘要
Abstract
New power systems are facing a contradiction between the rapid growth of renewable energy installation and the increasingly insufficient peak-shaving capacity.The coordinated allocation issue of renewable energy generation and peak-shaving resources needs to be solved at the planning stage,meeting the demands of autonomous peak-shaving.A method for characterizing the grid-connection boundary conditions for autonomous peak-shaving is proposed.Based on the yearly sequential operation simulation,a system peak-shaving demand assessment and a verification model for autonomous peak-shaving principle of newly connected units are constructed.Furthermore,an optimal capacity allocation model for wind-thermal-load-storage under the principle of autonomous peak-shaving is proposed.The bundling allocation scheme is achieved through iteratively solving production optimization problem of flexible loads,the optimization of wind-thermal-storage capacity,and the verification of autonomous peak-shaving principle.Analysis shows that optimal load-production sequencing strategies are superior to equal-interval production methods,thereby maximizing the ability to match fluctuations in wind power.The proposed planning scheme neither increases the system peak-shaving demand nor influences the consumption of original renewable energy generation.Multiple newly connected units planned in parallel can still satisfy the autonomous peak-shaving principle when being connected to the system simultaneously.The proposed method can realize sustainable planning of renewable energy generation.关键词
调峰/容量配置/灵活负荷/新能源发电/风火荷储打捆规划Key words
peak-shaving/capacity allocation/flexible load/renewable energy generation/wind-thermal-load-storage bundling planning引用本文复制引用
孙勇,王博闻,郑书坤,张忠..自主调峰下风火荷储容量优化配置方法[J].电力系统自动化,2026,50(8):106-115,10.基金项目
国家重点研发计划资助项目(2022YFB2404000) （2022YFB2404000）
国网吉林省电力有限公司科技项目(SGTYHT/23-JS-001). This work is supported by National Key R&D Program of China(No.2022YFB2404000)and State Grid Jilin Electric Power Co.,Ltd.(No.SGTYHT/23-JS-001). （SGTYHT/23-JS-001）
